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The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

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The Role of Statistics Post- Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006
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Page 1: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

The Role of Statistics Post-Market

Jay Herson, Ph.D.Johns Hopkins University

Sept 29, 2006

Page 2: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Post-Market Trials

• Phase IV• Label extension or modification• Surveillance• Investigator INDs• Seeding Studies• Biostatistician input much needed

Page 3: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Roles

• Role should not be described as a list of tasks

• Role of the biostatistician in post-market industry trials is to be an advocate for GOOD SCIENCE.

Page 4: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Wisdom

• Good Science is Good Business but• Good Business is not necessarily

good science• Credible and timely results is good

business in the long run

Page 5: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Good Science—Design Stage

• Objectives• Primary and secondary endpoints• Eligibility• Power and precision• Doses, regimens• Control Group• Non-inferiority trials

Page 6: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Good Science--Results

• Results available to patients and physicians

• Publication regardless of results• Clear definition of original objectives

of the trial• Appropriate measures of precision,

exposure• Post-hoc power

Page 7: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Advocate

• Independent Review throughout the trial

Page 8: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Post Market Trials

Then and Now

Page 9: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Large Trials

• GUSTO—t-PA vs streptokinase• ATLAS—adjuvant tamoxifen• COMMIT—acute MI asparin vs

clopidogrel• CPPT—lipids, cholestiramine• CONCORDE—HIV, AZT• WHI

Page 10: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Surprising Results

• BHAT—propranalol• CAST—encainide, flecainide

Page 11: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Cooperative Meta Analyses

• ATT—antithrombolytics• EBCTCG—early breast cancer

Page 12: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Oncology—Practice Changing Trials

• Aromatase inhibators—breast cancer• bevacizumab-VEGF, colorectal• trastuzimab—breast cancer• taxanes—lung, ovarian• platinum—lung ovarian

Page 13: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

However….• Most of the trials just referenced

were not conducted by industry

Page 14: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Industry Sponsorship

• Pre-Market---Science / Regulatory driven

• Post-Market—Marketing driven

Page 15: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Marketing Influence

• No trials undertaken whose results could threaten market share

• Results suppressed if they threaten market share

Page 16: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Industry Sponsorship• Phase IV—Under control of marketing• Anti-depressants—19/21 trials head-

to-head sponsors product superior.– Low dose for competitor– Different schedules– Simple conditions– Not double blind

Page 17: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

The Non-Inferiority Complex

• Sloppy trials• Result is under control of sponsor• Delta• Active control• Sub-potent dose• Terminate before effects• Imprecise measurement

Page 18: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Industry Sponsorship

• Publication bias• Results not matched with original

objectives• Cox-2 inhibitor trials / bureaucracy

Page 19: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Industry Sponsorship

• Advertising agency purchased CRO• Seeding studies• Design problems• Organizational problems

Page 20: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Good News

• William Olson, Ortho-McNeil• Patent 6,339,105• A regimen for the administration of

tramadol for the treatment of analgesia

• Slower titration rate• Reduction in side effects

Page 21: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Opportunities

• Bayesian design and analysis• Testing grounds—adaptive designs• Meta analysis

– Methodology– Fixed vs Random Effects– Mixed models

Page 22: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

A. Mugglin—Medical Devices

• Fine illustration of the role of statisticians

• Interesting SCD-HeFT cost-effectiveness study

• How do results of this information get disseminated to stakeholders—patients and their caregivers?

• Should not be used as sole justification for higher prices for the product.

Page 23: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Mugglin--Future

• Globalization• Aging of populations• Cost-effectiveness• IOM recommendation• Genetics

Page 24: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Genetics• Revisit approved but unpopular

drugs due to knowledge of what DNA is associated with response, low toxicity.

• bucindolol vs other beta blockers for heart failure

• tamoxifen vs aromatase inhibitors in breast cancer

Page 25: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Gould--Surveillance

• fialuridine (FIAU), 1993• Good list of limitations

(Considerations and Issues)• Accumulating information of RR and

the lower 5% point---how long to watch a signal?

• Retrospective pharmacovigilence

Page 26: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Gould--Bayes

• Definitely a role for Bayesian methods here. The sooner the better.

• Empirical Bayes a good start• Sponsor safety database• Oncology—MedDRA vs CTC 3.0

Page 27: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Gould--Contribution

• Shows the contribution a statistician can make to a difficult problem by thinking through the problem

• Hope for a common ground between plaintiffs and industry

• To deny the implications of this type of analysis is to deny our ability to reason

Page 28: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

Marinac-Dabic FDA/CDRH

• Sources of data• Areas requiring attention• Motivate good science• Post-market surveillance for the

elderly• Passive reporting system for high

quality post-market surveillance data

Page 29: The Role of Statistics Post-Market Jay Herson, Ph.D. Johns Hopkins University Sept 29, 2006.

• Thank You


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